Workshop Organizers

Aims and Scope

MAS and Complex Networks:

Multi Agent Systems (MAS) allow to study the emergence of
systemic properties which result from the interaction of a
large number of agents, rather than from single agents.
Intelligence can be seen as such an emergent property. This
means that the ability of a system to solve a problem, to optimize an
outcome, or to adapt to a changing situation in a prospective manner
may not be traced back to individual capabilities, but to the
collective effort of many agents. A framework to model these MAS is
provided by the complex networks approach, where agents are
represented by nodes and their interactions are represented by
links. Thus, the underlying network structure of a MAS plays a crucial
role in explaining emergent properties. Networked agents, on the other
hand, may be able to actively change this structure by forming new
links or cutting existing ones. Consequently, there is not only a
strong relation, but a coevolution in the dynamics of agents and their
network of interactions.

The aim of this workshop is to investigate the role of networked
agents in the emergence of systemic properties, notably emergent
intelligence. Focus is on topics such as network formation among
agents, feedback of network structures on agents dynamics,
network-based collective phenomena, and emergent problem solving by
networked agents.

Bridge Communities, Develop Commonalities:

Currently, it seems that research on MAS is still mostly focused on
agents themselves, whereas networks of agents have received relatively
little attention. The rapid development of various technologies,
including those in ubiquitous computing, sensor networks, and grid
computing will lead to systems consisting of a potentially very large
number of agents. In these situations, the view of each agent is
limited to its local environment, and the efficiency of the system is
significantly affected by the network in which the agents are
embedded. Thus, it is important to pay attention not only to agents
themselves, but also to the structure and the dynamics of the
network.

Traditionally, these topics have been addressed by researchers in
the field of network science. Currently, however, network science has
much more affinity to the community of complex systems research than
to the one of MAS. The intention of this workshop is to change this
by bridging the gap between the two research communities in
complex networks and multi-agent systems.

Thus, the workshop shall contribute to the development of an active
multi-disciplinary community by (i) increasing the mutual
awareness of researchers in the MAS and complex network communities,
(ii) building a foundation for combining agent-based modeling and
complex networks, (iii) developing predictive methodologies that can
be used to study the emergent intelligence of networked agents.

Overcome Limitations of Singular Approaches:

Research on complex networks focuses, among others, on the
scale-free properties of various kinds of networks. The absense of a
characteristic scale implies that the insights obtained can be scaled
up to large systems. Such properties may be of use for the study of
very large-scale MAS, where agents follow local rules under
complex network constraints. Their high-dimensional, non-linear nature
makes network-centric MAS difficult or impossible to analyze
with traditional methods. Thus, combining MAS and complex networks
could result into engineering methodologies to design
large-scale complex agent networks.

So far, our capabilities to model, understand, and predict the
behavior of networked agents do not fully meet the requirements of
large-scale systems. In order to explain the, sometimes
counter-intuitive, dynamics observed on the systemic level of large
MAS, we need to better know the relation between emergent properties
and the key mechanisms involved in shaping an agent's behavior. In
this respect, computational models play a substantial role. The
combined efforts in hardware development for simulating large MAS and
the understanding of large-scale interaction models will allow us to
reach the goal of developing a concise engineering methodology. The
workshop is intended as an important step into this direction, by
addressing the theoretical challenges of such large-scale networked
agent models.

Topics of Interest

All are with respect to multi-agent systems and complex networks:

Adaptation and evolution

Emergence in multi-agent systems

Collective intelligence

Learning and evolution

Social and economic agents

Multi-agent-based supply networks

Web dynamics

Network-centric agent systems

Scalability

Systemic risk in large-scale networks

Program and Schedule

The following is the tentative program and schedule; we will update
this as necessary. The workshop will take place in the Dufferin Room,
Second Floor, Sheraton Centre Toronto Hotel.

Registration

There is a reduced early registration fee until 12 March 2010; the
regular registration fee deadline is 9 April 2010; the late
registration fee is due after 9 April 2010 and for onsite
registration.

Submission and Deadlines

Please follow the guidelines of AAMAS 2010 (including the 8 page
maximum) for paper submissions to WEIN 2010. Submissions will
be peer reviewed in line with the standards of the main AAMAS 2010
conference.

All papers will be assembled into workshop proceedings and included
with the AAMAS 2010 conference proceedings; selected contributions of
the workshop will be published as regular papers in ACS - Advances
in Complex Systems.

For the camera-ready versions of papers, please use the SIG-alternate
style file, i.e. Option 2 of the SIG
Proceedings Templates, and include the following line in your LaTeX
code, filling in AUTHOR(S) and TITLE accordingly:

History

The WEIN Workshop series started as a Japanese initiative and has
been part of AAMAS regularly since 2006. Recent proceedings have
appeared, e.g., in the Springer Series on Studies in Computational
Intelligence or in the International Transactions on Systems Science
and Applications. WEIN 2010 will be the Fifth International Workshop
on Emergent Intelligence on Networked Agents. One of WEIN's core goals
is to bridge between the MAS and the complex network communities.

Important Note:
The content in this site is accessible to any browser or Internet device, however, some graphics will display correctly only in the newer versions of Netscape. To get the most out of our site we suggest you upgrade to a newer browser.More information